Behavioral aspects of nurse practitioners associated with optimal multiple sclerosis care in Spain
Bibliographic record
Abstract
BACKGROUND: Nurse practitioners (NPs) play a critical role in the multidisciplinary management of patients with multiple sclerosis (MS). Neurologists´ behavioral characteristics have been associated with suboptimal clinical decisions. However, limited information is available on their impact among NPs involved in MS care. The aim of this study was to assess nurses´ therapeutic choices to understand behavioral factors influencing their decision making process. METHODS: A non-interventional, cross-sectional, web-based study was conducted. NPs actively involved in the care of patients with MS were invited to participate in the study by the Spanish Society of Neurology Nursing. Participants answered questions regarding their standard practice and therapeutic management of seven simulated relapsing-remitting MS (RRMS) case scenarios. A behavioral battery was used to measure participants´ life satisfaction, mood, positive social behaviors, feeling of helpfulness, attitudes toward adoption of evidence-based innovations, occupational burnout, and healthcare-related regret. The outcome of interest was therapeutic inertia (TI), defined as the lack of treatment escalation when there is clinical and radiological evidence of disease activity. A score to quantify TI was created based on the number of simulated scenarios where treatment intensification was warranted. RESULTS: Overall, 331 NPs were invited to participate, 130 initiated the study, and 96 (29%) completed the study. The mean age (SD) was 44.6 (9.8) years and 91.7% were female. Seventy-three participants (76.0%) felt their opinions had a significant influence on neurologists´ therapeutic decisions. Sixteen NPs (16.5%) showed severe emotional exhaustion related to work and 13 (13.5%) had depressive symptoms. The mean (SD) TI score was 0.97 (1.1). Fifty-six of NPs showed TI in at least one case scenario. Higher years of nursing experience (p = 0.014), feeling of helpfulness (p = 0.014), positive attitudes toward innovations (p = 0.046), and a higher intensity of care-related regret (p = 0.021) were associated with a lower risk of TI (adjusted R2 = 0.28). Burnout was associated with higher risk of TI (p = 0.001). CONCLUSIONS: Although NPs cannot prescribe MS treatments in Spain, their behavioral characteristics may influence the management of patients with RRMS. Continuing education and specific strategies for reducing occupational burnout may lead to better management skills and improve MS care.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".